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Outline:Supervised Learning About Machine Learning and its types. About iris species and its measurement parameters. Load the iris dataset and libraries. How to pose a Machine Learning problem? About supervised learning and its types. About Naive Bayes classifier. Use the test set to evaluate the performance of the model. Train a classification model with a Naive Bayes classifier. Confusion matrix and its use. Check the accuracy using True positive and True negative values.
Supervised Learning About Machine Learning and its types. About iris species and its measurement parameters. Load the iris dataset and libraries. How to pose a Machine Learning problem? About supervised learning and its types. About Naive Bayes classifier. Use the test set to evaluate the performance of the model. Train a classification model with a Naive Bayes classifier. Confusion matrix and its use. Check the accuracy using True positive and True negative values.
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